An AI agent is one program: a model in a loop that picks tools to reach a goal you set. Agentic AI is the broader label for systems built that way, often several agents plus an orchestrator, memory and approval steps. Every agent is agentic; not every agentic system is a single agent.
| Question | AI agent | Agentic AI |
|---|---|---|
| What the term names | A single working program | A design approach or a whole system |
| Typical shape | One model, one loop, a handful of tools | Several agents, a coordinator, shared memory, checkpoints |
| Scope of a goal | One task, such as triaging an inbox | A process, such as handling an order end to end |
| Who sets the plan | The agent, within the tools it has | A planner splits work and hands parts to agents |
| Where failures show | A bad tool choice or a loop that will not stop | Hand-offs between agents and conflicting actions |
| Is it a product? | Often sold as one | Usually a description, not a product |
Updated
Neither phrase has an official definition from a standards body, so vendors stretch both. The working definitions above are the ones most engineers would recognise. Test yourself on the quiz below: each scenario is one of the two, or neither.
Both snippets use a stub in place of a model so they run in Node as they are. The shape is what matters: one loop versus a coordinator handing work to several loops.
makeAgent returns a small loop with its own tools. The coordinator decides the order and holds the approval step.
function makeAgent(name, tools) {
return async (task) => {
// A real agent would ask a model which tool to call; this stub uses the first.
const [toolName, run] = Object.entries(tools)[0];
const result = await run(task);
return `${name} used ${toolName}: ${result}`;
};
}
// An AI agent: one loop, its own tools.
const researcher = makeAgent("researcher", {
search_docs: async (q) => `3 documents mention "${q}"`,
});
// An agentic system: a coordinator, two agents and an approval point.
const writer = makeAgent("writer", {
draft: async (notes) => `draft based on [${notes}]`,
});
async function coordinator(goal, approve) {
const notes = await researcher(goal);
const draft = await writer(notes);
return (await approve(draft)) ? draft : "Held for review";
}
coordinator("return policy", async () => true).then(console.log);A useful way to sort real systems is by who picks the next step. In plain automation, your code fixes every step and the model only fills in text. In an agent, the model picks the next step from the tools you allow.
In a multi-agent or agentic system, a planner also decides which agent takes which part of the job. Each level adds flexibility and adds places where things can go wrong.
A product called an agent may be a single loop you can reason about in an afternoon. A product called agentic may coordinate many loops, each with its own permissions. Testing, cost and risk scale with the number of loops.
So ask for the tool list, the permission model and the approval points before comparing two offerings by their labels.
Partly. It describes a real pattern, models that act through tools over several steps, but the label is also applied to tools that only fill in a template. Ask what decisions the software makes on its own.
Not by itself. An assistant that only replies with text has no actions. It becomes an agent when it can call tools, see the results and decide the next step toward a goal.
No. A single agent with a planner, memory and approval steps is agentic too. Several agents appear when a job is easier to split, such as one agent that researches and another that writes.
Usually a single agent with one narrow job, such as sorting incoming requests. It is cheaper to run, easier to test and simpler to stop. Bigger multi-agent setups pay off only for long, repeated processes.
The OWASP GenAI Security Project publishes the Top 10 for LLM Applications 2025, which includes Excessive Agency, and released an Agentic AI Threats and Mitigations guide in February 2025.
Related: How to build an AI agent, What is an MCP server?, AI agent test checklist, AI agent script template.
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